SoroushVahidi/scidocs huggingface dataset:
DSD: Dense-Sparse-Dense Training for Deep Neural Networks
(2017)

Modern deep neural networks have a large number of parameters, making them very hard to train. We propose DSD, a dense-sparse-dense training flow, for regularizing deep neural networks and achieving better optimization performance. In the first D (Dense) step, we train a dense network to learn connection weights and importance. In the S (Sparse) step, we regularize the network by pruning the unimportant connections with small weights and retraining the network given the sparsity constraint. In the final D (re-Dense) step, we increase the model capacity by removing the sparsity constraint, re-initialize the pruned parameters from zero and retrain the whole dense network. Experiments show that DSD training can improve the performance for a wide range of CNNs, RNNs and LSTMs on the tasks of image classification, caption generation and speech recognition. On ImageNet, DSD improved the Top1 accuracy of GoogLeNet by 1.1%, VGG-16 by 4.3%, ResNet-18 by 1.2% and ResNet-50 by 1.1%, respectively. On the WSJ’93 dataset, DSD improved DeepSpeech and DeepSpeech2 WER by 2.0% and 1.1%. On the Flickr-8K dataset, DSD improved the NeuralTalk BLEU score by over 1.7. DSD is easy to use in practice: at training time, DSD incurs only one extra hyper-parameter: the sparsity ratio in the S step. At testing time, DSD doesn’t change the network architecture or incur any inference overhead. The consistent and significant performance gain of DSD experiments shows the inadequacy of the current training methods for finding the best local optimum, while DSD effectively achieves superior optimization performance for finding a better solution. DSD models are available to download at https://songhan.github.io/DSD.
High quality information provisioning and data pricing
(2013)

This paper presents ideas on how to advance the research on high quality information provisioning and information pricing. To this end, the current state of the art in combining data curation and information provisioning as well as in regard to data pricing is reviewed. Based on that, open issues, such as tailoring data to a user's need and determining a market value of data, are identified. As preliminary solutions, it is proposed to investigate the identified problems in an integrated manner.
Chukwa: A large-scale monitoring system
(2008)

We describe the design and initial implementation of Chukwa, a data collection system for monitoring and analyzing large distributed systems. Chukwa is built on top of Hadoop, an open source distributed filesystem and MapReduce implementation, and inherits Hadoop’s scalability and robustness. Chukwa also includes a flexible and powerful toolkit for displaying monitoring and analysis results, in order to make the best use of this collected data.
Role of Procedural Justice , Organizational Commitment and Job Satisfaction on job Performance : The Mediating Effects of Organizational Citizenship Behavior
(2013)

The study examines the impact of procedural justice, organizational commitment, job satisfaction on employee performance, and the potential mediating role played by organization citizenship behaviors in that process. This model was tested using a sample of 70 employees embedded in 2 groups from 15 branches of a large, syariah bank in Malang. The sample is taken using proportional random sampling. Data is collected directly from respondents using questionnaires and technical data analysis using GeSCA. The study results showed that both procedural justice and organizational commitment positively affected Organizational Citizenship Behavior. Organizational commitments do positive influence job performance. Job satisfaction did not positively influence Organizational Citizenship Behavior and job performance. Organizational Citizenship behavior positively influences job performance. Organizational Citizenship behavior acted as a partial mediator between procedural justice, organizational commitment, and job performance. A number of suggestions on managerial theory and implementation were proposed.
Substrate-Integrated Two-Port Dual-Frequency Antenna
(2016)

A two-port dual-frequency substrate-integrated antenna with a large frequency difference is presented. It consists of a differentially fed slot antenna and a substrate-integrated dielectric resonator antenna for low- and high-frequency radiation, respectively. The former is loaded by a hollow patch, whereas the latter is fabricated inside the hollow region of the patch by using air holes and metalized vias. Beneath the antenna substrate is a second substrate on which slot-coupled sources are printed to feed the two antennas. For demonstration, a two-port dual-frequency antenna working at 5.2-GHz WLAN band and 24-GHz ISM band was designed, fabricated, and measured. The S-parameters, radiation patterns, and antenna gains of the two antenna parts are reported. Reasonable agreement between the measured and simulated results is observed. Very good isolation of over 35 dB between the two antenna parts is observed.
Balanced Multithreading: Increasing Throughput via a Low Cost Multithreading Hierarchy
(2004)

A simultaneous multithreading (SMT) processor can issue instructions from several threads every cycle, allowing it to effectively hide various instruction latencies; this effect increases with the number of simultaneous contexts supported. However, each added context on an SMT processor incurs a cost in complexity, which may lead to an increase in pipeline length or a decrease in the maximum clock rate. This paper presents new designs for multithreaded processors which combine a conservative SMT implementation with a coarse-grained multithreading capability. By presenting more virtual contexts to the operating system and user than are supported in the core pipeline, the new designs can take advantage of the memory parallelism present in workloads with many threads, while avoiding the performance penalties inherent in a many-context SMT processor design. A design with 4 virtual contexts, but which is based on a 2-context SMT processor core, gains an additional 26% throughput when 4 threads are run together.
Can machine learning aid in delivering new use cases and scenarios in 5G?
(2016)

5G represents the next generation of communication networks and services, and will bring a new set of use cases and scenarios. These in turn will address a new set of challenges from the network and service management perspective, such as network traffic and resource management, big data management and energy efficiency. Consequently, novel techniques and strategies are required to address these challenges in a smarter way. In this paper, we present the limitations of the current network and service management and describe in detail the challenges that 5G is expected to face from a management perspective. The main contribution of this paper is presenting a set of use cases and scenarios of 5G in which machine learning can aid in addressing their management challenges. It is expected that machine learning can provide a higher and more intelligent level of monitoring and management of networks and applications, improve operational efficiencies and facilitate the requirements of the future 5G network.
Hierarchical Multi-label Conditional Random Fields for Aspect-Oriented Opinion Mining
(2014)

A common feature of many online review sites is the use of an overall rating that summarizes the opinions expressed in a review. Unfortunately, these document-level ratings do not provide any information about the opinions contained in the review that concern a specific aspect (e.g., cleanliness) of the product being reviewed (e.g., a hotel). In this paper we study the finer-grained problem of aspect-oriented opinion mining at the sentence level, which consists of predicting, for all sentences in the review, whether the sentence expresses a positive, neutral, or negative opinion (or no opinion at all) about a specific aspect of the product. For this task we propose a set of increasingly powerful models based on conditional random fields (CRFs), including a hierarchical multi-label CRFs scheme that jointly models the overall opinion expressed in the review and the set of aspect-specific opinions expressed in each of its sentences. We evaluate the proposed models against a dataset of hotel reviews (which we here make publicly available) in which the set of aspects and the opinions expressed concerning them are manually annotated at the sentence level. We find that both hierarchical and multi-label factors lead to improved predictions of aspect-oriented opinions.
International Telecommunication Union. Systems Management: Summarization function. Recommendation X.738
(2004)

Prepaid mobile phone plans are gaining in importance in the U.S. and are already well established in Europe. Aggregation of a certain number of Micropayments is the preferred business model for wireless carriers to leverage the existing payment infrastructure with a mobile payment solution. There exist various Payment Scenarios that are based on the Wallet metaphor, and in general, they can be used to implement flexible and scalable solutions. Person-to-person transactions are already very popular in the U.S. as a consequence of the widespread use a payment instrument for auctions at eBay. This scenario is most often discussed as a valuable alternative to check payments in the U.S. For several reasons, the U.S. has been slower to adopt wireless technology than Europe. First, landlines in the U.S. are dominant and high personal computer penetration prevents people from using mobile phones to communicate, either by voice calls or text messaging. Second, prices in the U.S. favor landlines, even though prices for mobile phone plans in the competitive market have been cut many times in the past. For mobile payment, the fact that social patterns matter could affect the adoption of this form of payment in Europe, because in several countries, solutions already exist. The factors that form the concept of Diffusion of Innovation Theory eventually can be seen as the critical success factors of mobile payment. ii Whereas some emerging and existing mobile payment systems will come along with their own processing infrastructure, several will be based on existing payment networks that have initially been designed for another purpose. In Europe, credit card operators launch mobile payment solutions to leverage their existing networks while in the U.S., operators of ATM networks and leading credit card processors even try to bypass existing networks. Unlike in Europe, where checks have de facto been banned from the market by charging high prices for the processing of this non-cash payment instrument, the U.S. partly supports innovative check processing solutions to leverage the ACH infrastructure. The European bank approach shows that customer's payment behavior can be influenced by a pricing policy. Meanwhile, European countries and the U.S. have switched to 2.5G networks. With the transition to 3G, interoperability within the U.S. should finally become reality. Commercial launches of 3G services have already started in both regions. Notably, the first U.S. carrier to launch a broadband wireless service seems to be attracting business customers and offering high …
A Systematic Gap Analysis of Social Engineering Defence Mechanisms Considering Social Psychology
(2016)

Social engineering is the acquisition of information about computer systems by methods that deeply include non-technical means. While technical security of most critical systems is high, the systems remain vulnerable to attacks from social engineers. Social engineering is a technique that: (i) does not require any (advanced) technical tools, (ii) can be used by anyone, (iii) is cheap. Traditional penetration testing approaches often focus on vulnerabilities in network or software systems. Few approaches even consider the exploitation of humans via social engineering. While the amount of social engineering attacks and the damage they cause rise every year, the defences against social engineering do not evolve accordingly. Hence, the security awareness of these attacks by employees remains low. We examined the psychological principles of social engineering and which psychological techniques induce resistance to persuasion applicable for social engineering. The techniques examined are an enhancement of persuasion knowledge, attitude bolstering and influencing the decision making. While research exists elaborating on security awareness, the integration of resistance against persuasion has not been done. Therefore, we analysed current defence mechanisms and provide a gap analysis based on research in social psychology. Based on our findings we provide guidelines of how to improve social engineering defence mechanisms such as security awareness programs.
An innovative oscillometric blood pressure measurement: Getting rid of the traditional envelope
(2012)

Oscillometric blood pressure devices are popular and are considered part of the family's medical chest at home. The popularity of these devices for private use is not shared by physicians mainly due to the fact that the blood pressures are computed instead of measured. The classical way to compute the systolic and diastolic blood pressure is based on the envelope of the oscillometric waveform. The algorithm to compute the blood pressures from the waveform is firm dependent, often patented and lacks scientific foundation. In this paper, we propose a totally new approach. Instead of the envelope of the oscillometric waveform, we use a statistical test to pin-point the time instances where the systolic and diastolic blood pressures are measured in the cuff. This technique has the advantage of being mathematically well-posed instead of the ill-posed problem of envelope fitting. Hence, in order to calibrate the oscillometric blood pressure monitor it is sufficient to make the statistical test unbiased.
A new ultrawideband printed monopole antenna: the planar inverted cone antenna (PICA)
(2004)

A new antenna, the planar inverted cone antenna (PICA), provides ultrawideband (UWB) performance with a radiation pattern similar to monopole disk antennas , but is smaller in size. Extensive simulations and experiments demonstrate that the PICA antenna provides more than a 10:1 impedance bandwidth (for VSWR<2) and supports a monopole type omnidirectional pattern over 4:1 bandwidth. A second version of the PICA with two circular holes changes the current flow on the metal disk and extends the high end of the operating frequency range, improving the pattern bandwidth to 7:1.
Towards Implicit Content-Introducing for Generative Short-Text Conversation Systems
(2017)

The study on human-computer conversation systems is a hot research topic nowadays. One of the prevailing methods to build the system is using the generative Sequence-to-Sequence (Seq2Seq) model through neural networks. However, the standard Seq2Seq model is prone to generate trivial responses. In this paper, we aim to generate a more meaningful and informative reply when answering a given question. We propose an implicit content-introducing method which incorporates additional information into the Seq2Seq model in a flexible way. Specifically, we fuse the general decoding and the auxiliary cue word information through our proposed hierarchical gated fusion unit. Experiments on real-life data demonstrate that our model consistently outperforms a set of competitive baselines in terms of BLEU scores and human evaluation.
A 100 watts L-band power amplifier
(2017)

In this paper, a 1100–1350 MHz power amplifier is introduced. For the realization of the RF power amplifier an LDMOS transistor is used. The amplifier delivers 100W power to a 50 ohm load with 50% efficiency. The transducer power gain of the amplifier is has 16dB at 100W output power. A mixed lumped element and transmission line matching circuit is used to implement matching network. The simulations are performed by the nonlinear model of the transistor, which is provided by the manufacturer. Finally the results of simulations are compared with the measurements.
A design methodology for the realization of multi-decade baluns at microwave frequencies
(2011)

A new methodology is presented for designing baluns exhibiting multi-decade bandwidths at microwave frequencies. Simulations show that resistors terminating the outer transmission line suppress the half-wavelength resonance and greatly extend the bandwidth. Using linear measurements at microwave frequencies, ferrite beads have been shown to behave as resistors with a small reactance, suitable for terminating the outer transmission line. This paper shows that ferrite beads can perform the dual role of improving magnetic coupling at low frequency and suppressing resonance at higher frequencies. The design methodology was applied to produce a balun that operates between 30MHz and 6GHz, displays less than 1dB of power loss up to 4.4GHz, and delivers an impedance transformation of 2∶1.
100 W GaN HEMT power amplifier module with > 60% efficiency over 100–1000 MHz bandwidth
(2010)

We have demonstrated a decade bandwidth 100 W GaN HEMT power amplifier module with 15.5–18.6 dB gain, 104–121 W CW output power and 61.4–76.6 % drain efficiency over the 100–1000 MHz band. The 2 × 2 inch compact power amplifier module combines four 30 W lossy matched broadband GaN HEMT PAs packaged in a ceramic SO8 package. Each of the 4 devices is fully matched to 50 Ω and obtains 30.8–35.7 W with 68.6–79.6 % drain efficiency over the band. The packaged amplifiers contain a GaN on SiC device operating at 48V drain voltage, alongside GaAs integrated passive matching circuitry. The four devices are combined using a broadband low loss coaxial balun. We believe this combination of output power, bandwidth and efficiency is the best reported to date. These amplifiers are targeted for use in multi-band public mobile radios and for instrumentation applications.
10W ultra-broadband power amplifier
(2008)

We report the design and performance of an ultra-broadband power amplifier. It achieves 10 Watts output power with 21dB ± 1.5dB gain from 20 MHz to 3000 MHz. At lower frequencies from 20 to 1000 MHz the output power is 15 Watts with 22% efficiency. To achieve this performance, we employ a new design concept to control the device impedance and the power combiner impedance to be naturally 50 Ohms, such that no impedance matching is needed. Also, we developed a broadband microwave balun as a push-pull power combiner, which doubles as an impedance transformer. We believe the combination of output power, bandwidth and efficiency is the best reported to date.
Full-Body Compliant Human–Humanoid Interaction: Balancing in the Presence of Unknown External Forces
(2007)

This paper proposes an effective framework of human-humanoid robot physical interaction. Its key component is a new control technique for full-body balancing in the presence of external forces, which is presented and then validated empirically. We have adopted an integrated system approach to develop humanoid robots. Herein, we describe the importance of replicating human-like capabilities and responses during human-robot interaction in this context. Our balancing controller provides gravity compensation, making the robot passive and thereby facilitating safe physical interactions. The method operates by setting an appropriate ground reaction force and transforming these forces into full-body joint torques. It handles an arbitrary number of force interaction points on the robot. It does not require force measurement at interested contact points. It requires neither inverse kinematics nor inverse dynamics. It can adapt to uneven ground surfaces. It operates as a force control process, and can therefore, accommodate simultaneous control processes using force-, velocity-, or position-based control. Forces are distributed over supporting contact points in an optimal manner. Joint redundancy is resolved by damping injection in the context of passivity. We present various force interaction experiments using our full-sized bipedal humanoid platform, including compliant balance, even when affected by unknown external forces, which demonstrates the effectiveness of the method.
Neuropsychology and clinical neuroscience of persistent post-concussive syndrome.
(2008)

On the mild end of the acquired brain injury spectrum, the terms concussion and mild traumatic brain injury (mTBI) have been used interchangeably, where persistent post-concussive syndrome (PPCS) has been a label given when symptoms persist for more than three months post-concussion. Whereas a brief history of concussion research is overviewed, the focus of this review is on the current status of PPCS as a clinical entity from the perspective of recent advances in the biomechanical modeling of concussion in human and animal studies, particularly directed at a better understanding of the neuropathology associated with concussion. These studies implicate common regions of injury, including the upper brainstem, base of the frontal lobe, hypothalamic-pituitary axis, medial temporal lobe, fornix, and corpus callosum. Limitations of current neuropsychological techniques for the clinical assessment of memory and executive function are explored and recommendations for improved research designs offered, that may enhance the study of long-term neuropsychological sequelae of concussion.
Computer-aided generation of multiple-choice tests
(2003)

Summary form only given. The paper describes a novel automatic procedure for the generation of multiple-choice tests from electronic documents. In addition to employing various NLP techniques including term extraction and shallow parsing, the system makes use of language resources such as corpora and ontologies. The system operates in a fully automatic mode and also a semiautomatic environment where the user is offered the option to post-edit the generated test items. The results from the conducted evaluation suggest that the new procedure is very effective saving time and labour considerably and that the test items produced with the help of the program are not of inferior quality to those produced manually.
Model-Driven Reverse Engineering Approaches: A Systematic Literature Review
(2017)

This paper explores and describes the state of the art for what concerns the model-driven approaches proposed in the literature to support reverse engineering. We conducted a systematic literature review on this topic with the aim to answer three research questions. We focus on various solutions developed for model-driven reverse engineering, outlining in particular the models they use and the transformations applied to the models. We also consider the tools used for model definition, extraction, and transformation and the level of automation reached by the available tools. The model-driven reverse engineering approaches are also analyzed based on various features such as genericity, extensibility, automation of the reverse engineering process, and coverage of the full or partial source artifacts. We describe in detail and compare fifteen approaches applying model-driven reverse engineering. Based on this analysis, we identify and indicate some hints on choosing a model-driven reverse engineering approach from the available ones, and we outline open issues concerning the model-driven reverse engineering approaches.